{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom class to clean data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class clean_data:\n",
    "    data = pd.DataFrame()\n",
    "    nullcols = list()\n",
    "    cols = list()\n",
    "    nulldict = dict()\n",
    "    exclude = list()\n",
    "    l = 0\n",
    "    def __init__(self,data):\n",
    "        self.data = data\n",
    "        self.cols = self.data.columns\n",
    "        self.l = len(self.data)\n",
    "    def null_columns(self):\n",
    "        for i in self.cols:\n",
    "            if self.data[i].isnull().sum() > 0:\n",
    "                self.nullcols.append(i)\n",
    "                self.nulldict[i] = self.data[i].isnull().sum()\n",
    "        return self.nullcols\n",
    "    def exlude_null_value_cols(self):\n",
    "        for i,j in self.nulldict.items():\n",
    "            if j/len(self.data) * 100 >= 50:\n",
    "                self.exclude.append(i)\n",
    "                self.nullcols.remove(i)\n",
    "        return self.exclude\n",
    "    def print_nullcolumns(self):\n",
    "        print(self.nulldict)\n",
    "    def deal_with_numeric_null(self):\n",
    "        self.temp = self.data[self.nullcols]\n",
    "        self.temp = self.temp.loc[:,self.temp.dtypes == np.int64]\n",
    "        self.numcol = self.temp.columns\n",
    "        self.temp1 = self.data[self.nullcols]\n",
    "        self.temp1 = self.temp1.loc[:,self.temp1.dtypes == np.float64]\n",
    "        self.numcol1 = self.temp1.columns\n",
    "        for i in self.numcol:\n",
    "                m = self.data[i].mean()\n",
    "                self.data[i].fillna(m,inplace=True)\n",
    "        for i in self.numcol1:\n",
    "                m = self.data[i].mean()\n",
    "                self.data[i].fillna(m,inplace=True)\n",
    "        return self.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Custom class to Encode the categorical variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class encoder:\n",
    "    data = pd.DataFrame()\n",
    "    cols = list()\n",
    "    def __init__(self,data):\n",
    "        self.data = data.loc[:,data.dtypes == np.object]\n",
    "        self.cols = self.data.columns\n",
    "    def start_encoding(self):\n",
    "        for i in self.cols:\n",
    "            self.data[i] = self.data[i].astype('category').cat.codes\n",
    "        return self.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Function to check the correlation between Dependent and independent variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def corr_elemination(x,y):\n",
    "    col = list(x.columns)\n",
    "    lis = dict()\n",
    "    for i in col:\n",
    "        if x[i].corr(y) >= 0.5 or x[i].corr(y) <= -0.5:\n",
    "            lis[i] = x[i].corr(y)\n",
    "    return lis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>LandSlope</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Condition1</th>\n",
       "      <th>Condition2</th>\n",
       "      <th>BldgType</th>\n",
       "      <th>HouseStyle</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>RoofStyle</th>\n",
       "      <th>RoofMatl</th>\n",
       "      <th>Exterior1st</th>\n",
       "      <th>Exterior2nd</th>\n",
       "      <th>MasVnrType</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>ExterCond</th>\n",
       "      <th>Foundation</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>Heating</th>\n",
       "      <th>HeatingQC</th>\n",
       "      <th>CentralAir</th>\n",
       "      <th>Electrical</th>\n",
       "      <th>1stFlrSF</th>\n",
       "      <th>2ndFlrSF</th>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <th>GrLivArea</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <th>FullBath</th>\n",
       "      <th>HalfBath</th>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <th>Functional</th>\n",
       "      <th>Fireplaces</th>\n",
       "      <th>FireplaceQu</th>\n",
       "      <th>GarageType</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageCars</th>\n",
       "      <th>GarageArea</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>PavedDrive</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2003</td>\n",
       "      <td>2003</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>196.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>706</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>856</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>856</td>\n",
       "      <td>854</td>\n",
       "      <td>0</td>\n",
       "      <td>1710</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>8</td>\n",
       "      <td>Typ</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>548</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Veenker</td>\n",
       "      <td>Feedr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>1Story</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1976</td>\n",
       "      <td>1976</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>CBlock</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>978</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>284</td>\n",
       "      <td>1262</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>460</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2001</td>\n",
       "      <td>2002</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>162.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Mn</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>486</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>434</td>\n",
       "      <td>920</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>920</td>\n",
       "      <td>866</td>\n",
       "      <td>0</td>\n",
       "      <td>1786</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>608</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Crawfor</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1915</td>\n",
       "      <td>1970</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>Wd Sdng</td>\n",
       "      <td>Wd Shng</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>BrkTil</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>No</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>216</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>540</td>\n",
       "      <td>756</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>961</td>\n",
       "      <td>756</td>\n",
       "      <td>0</td>\n",
       "      <td>1717</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>7</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Detchd</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>3</td>\n",
       "      <td>642</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>272</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>NoRidge</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>2000</td>\n",
       "      <td>2000</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Av</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>655</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>490</td>\n",
       "      <td>1145</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1145</td>\n",
       "      <td>1053</td>\n",
       "      <td>0</td>\n",
       "      <td>2198</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>9</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>3</td>\n",
       "      <td>836</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>192</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities LotConfig LandSlope Neighborhood Condition1  \\\n",
       "0         Lvl    AllPub    Inside       Gtl      CollgCr       Norm   \n",
       "1         Lvl    AllPub       FR2       Gtl      Veenker      Feedr   \n",
       "2         Lvl    AllPub    Inside       Gtl      CollgCr       Norm   \n",
       "3         Lvl    AllPub    Corner       Gtl      Crawfor       Norm   \n",
       "4         Lvl    AllPub       FR2       Gtl      NoRidge       Norm   \n",
       "\n",
       "  Condition2 BldgType HouseStyle  OverallQual  OverallCond  YearBuilt  \\\n",
       "0       Norm     1Fam     2Story            7            5       2003   \n",
       "1       Norm     1Fam     1Story            6            8       1976   \n",
       "2       Norm     1Fam     2Story            7            5       2001   \n",
       "3       Norm     1Fam     2Story            7            5       1915   \n",
       "4       Norm     1Fam     2Story            8            5       2000   \n",
       "\n",
       "   YearRemodAdd RoofStyle RoofMatl Exterior1st Exterior2nd MasVnrType  \\\n",
       "0          2003     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "1          1976     Gable  CompShg     MetalSd     MetalSd       None   \n",
       "2          2002     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "3          1970     Gable  CompShg     Wd Sdng     Wd Shng       None   \n",
       "4          2000     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "\n",
       "   MasVnrArea ExterQual ExterCond Foundation BsmtQual BsmtCond BsmtExposure  \\\n",
       "0       196.0        Gd        TA      PConc       Gd       TA           No   \n",
       "1         0.0        TA        TA     CBlock       Gd       TA           Gd   \n",
       "2       162.0        Gd        TA      PConc       Gd       TA           Mn   \n",
       "3         0.0        TA        TA     BrkTil       TA       Gd           No   \n",
       "4       350.0        Gd        TA      PConc       Gd       TA           Av   \n",
       "\n",
       "  BsmtFinType1  BsmtFinSF1 BsmtFinType2  BsmtFinSF2  BsmtUnfSF  TotalBsmtSF  \\\n",
       "0          GLQ         706          Unf           0        150          856   \n",
       "1          ALQ         978          Unf           0        284         1262   \n",
       "2          GLQ         486          Unf           0        434          920   \n",
       "3          ALQ         216          Unf           0        540          756   \n",
       "4          GLQ         655          Unf           0        490         1145   \n",
       "\n",
       "  Heating HeatingQC CentralAir Electrical  1stFlrSF  2ndFlrSF  LowQualFinSF  \\\n",
       "0    GasA        Ex          Y      SBrkr       856       854             0   \n",
       "1    GasA        Ex          Y      SBrkr      1262         0             0   \n",
       "2    GasA        Ex          Y      SBrkr       920       866             0   \n",
       "3    GasA        Gd          Y      SBrkr       961       756             0   \n",
       "4    GasA        Ex          Y      SBrkr      1145      1053             0   \n",
       "\n",
       "   GrLivArea  BsmtFullBath  BsmtHalfBath  FullBath  HalfBath  BedroomAbvGr  \\\n",
       "0       1710             1             0         2         1             3   \n",
       "1       1262             0             1         2         0             3   \n",
       "2       1786             1             0         2         1             3   \n",
       "3       1717             1             0         1         0             3   \n",
       "4       2198             1             0         2         1             4   \n",
       "\n",
       "   KitchenAbvGr KitchenQual  TotRmsAbvGrd Functional  Fireplaces FireplaceQu  \\\n",
       "0             1          Gd             8        Typ           0         NaN   \n",
       "1             1          TA             6        Typ           1          TA   \n",
       "2             1          Gd             6        Typ           1          TA   \n",
       "3             1          Gd             7        Typ           1          Gd   \n",
       "4             1          Gd             9        Typ           1          TA   \n",
       "\n",
       "  GarageType  GarageYrBlt GarageFinish  GarageCars  GarageArea GarageQual  \\\n",
       "0     Attchd       2003.0          RFn           2         548         TA   \n",
       "1     Attchd       1976.0          RFn           2         460         TA   \n",
       "2     Attchd       2001.0          RFn           2         608         TA   \n",
       "3     Detchd       1998.0          Unf           3         642         TA   \n",
       "4     Attchd       2000.0          RFn           3         836         TA   \n",
       "\n",
       "  GarageCond PavedDrive  WoodDeckSF  OpenPorchSF  EnclosedPorch  3SsnPorch  \\\n",
       "0         TA          Y           0           61              0          0   \n",
       "1         TA          Y         298            0              0          0   \n",
       "2         TA          Y           0           42              0          0   \n",
       "3         TA          Y           0           35            272          0   \n",
       "4         TA          Y         192           84              0          0   \n",
       "\n",
       "   ScreenPorch  PoolArea PoolQC Fence MiscFeature  MiscVal  MoSold  YrSold  \\\n",
       "0            0         0    NaN   NaN         NaN        0       2    2008   \n",
       "1            0         0    NaN   NaN         NaN        0       5    2007   \n",
       "2            0         0    NaN   NaN         NaN        0       9    2008   \n",
       "3            0         0    NaN   NaN         NaN        0       2    2006   \n",
       "4            0         0    NaN   NaN         NaN        0      12    2008   \n",
       "\n",
       "  SaleType SaleCondition  SalePrice  \n",
       "0       WD        Normal     208500  \n",
       "1       WD        Normal     181500  \n",
       "2       WD        Normal     223500  \n",
       "3       WD       Abnorml     140000  \n",
       "4       WD        Normal     250000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('train_house.csv')\n",
    "pd.set_option('display.max_columns',len(df.columns))\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x23b00febfd0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot('SaleCondition','SalePrice',data=df,kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x23b030e3780>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot('SaleCondition','SalePrice',data=df,col='SaleType',kind='bar',col_wrap=3,legend=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23b03985128>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot('SaleCondition',data=df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x23b038d2780>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1080 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot('SaleCondition','SalePrice',data=df,kind='line',ci=False,col='YrSold',col_wrap=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x23b03f41780>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 801.234x1080 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot('SaleCondition','SalePrice',data=df,ci=False,col='YrSold',hue='YearBuilt',col_wrap=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x23b03369d68>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot('MSZoning','SalePrice',data=df,kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# data wrangling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id               0\n",
       "MSSubClass       0\n",
       "MSZoning         0\n",
       "LotFrontage    259\n",
       "LotArea          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23b047898d0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "sns.heatmap(df.isnull(),yticklabels=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "clean = clean_data(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['LotFrontage',\n",
       " 'Alley',\n",
       " 'MasVnrType',\n",
       " 'MasVnrArea',\n",
       " 'BsmtQual',\n",
       " 'BsmtCond',\n",
       " 'BsmtExposure',\n",
       " 'BsmtFinType1',\n",
       " 'BsmtFinType2',\n",
       " 'Electrical',\n",
       " 'FireplaceQu',\n",
       " 'GarageType',\n",
       " 'GarageYrBlt',\n",
       " 'GarageFinish',\n",
       " 'GarageQual',\n",
       " 'GarageCond',\n",
       " 'PoolQC',\n",
       " 'Fence',\n",
       " 'MiscFeature']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "null_cols = clean.null_columns()\n",
    "null_cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Alley', 'PoolQC', 'Fence', 'MiscFeature']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exl_cols = clean.exlude_null_value_cols()\n",
    "exl_cols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(exl_cols,axis=1,inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "77"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23b04a6c0f0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "sns.heatmap(df.isnull(),yticklabels=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>LandSlope</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Condition1</th>\n",
       "      <th>Condition2</th>\n",
       "      <th>BldgType</th>\n",
       "      <th>HouseStyle</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>RoofStyle</th>\n",
       "      <th>RoofMatl</th>\n",
       "      <th>Exterior1st</th>\n",
       "      <th>Exterior2nd</th>\n",
       "      <th>MasVnrType</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>ExterCond</th>\n",
       "      <th>Foundation</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>Heating</th>\n",
       "      <th>HeatingQC</th>\n",
       "      <th>CentralAir</th>\n",
       "      <th>Electrical</th>\n",
       "      <th>1stFlrSF</th>\n",
       "      <th>2ndFlrSF</th>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <th>GrLivArea</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <th>FullBath</th>\n",
       "      <th>HalfBath</th>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <th>Functional</th>\n",
       "      <th>Fireplaces</th>\n",
       "      <th>FireplaceQu</th>\n",
       "      <th>GarageType</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageCars</th>\n",
       "      <th>GarageArea</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>PavedDrive</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2003</td>\n",
       "      <td>2003</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>196.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>706</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>856</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>856</td>\n",
       "      <td>854</td>\n",
       "      <td>0</td>\n",
       "      <td>1710</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>8</td>\n",
       "      <td>Typ</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>548</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Veenker</td>\n",
       "      <td>Feedr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>1Story</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1976</td>\n",
       "      <td>1976</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>CBlock</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>978</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>284</td>\n",
       "      <td>1262</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>460</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2001</td>\n",
       "      <td>2002</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>162.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Mn</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>486</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>434</td>\n",
       "      <td>920</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>920</td>\n",
       "      <td>866</td>\n",
       "      <td>0</td>\n",
       "      <td>1786</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>608</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Crawfor</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1915</td>\n",
       "      <td>1970</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>Wd Sdng</td>\n",
       "      <td>Wd Shng</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>BrkTil</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>No</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>216</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>540</td>\n",
       "      <td>756</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>961</td>\n",
       "      <td>756</td>\n",
       "      <td>0</td>\n",
       "      <td>1717</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>7</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Detchd</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>3</td>\n",
       "      <td>642</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>272</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>NoRidge</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>2000</td>\n",
       "      <td>2000</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Av</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>655</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>490</td>\n",
       "      <td>1145</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1145</td>\n",
       "      <td>1053</td>\n",
       "      <td>0</td>\n",
       "      <td>2198</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>9</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>3</td>\n",
       "      <td>836</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>192</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street LotShape LandContour  \\\n",
       "0   1          60       RL         65.0     8450   Pave      Reg         Lvl   \n",
       "1   2          20       RL         80.0     9600   Pave      Reg         Lvl   \n",
       "2   3          60       RL         68.0    11250   Pave      IR1         Lvl   \n",
       "3   4          70       RL         60.0     9550   Pave      IR1         Lvl   \n",
       "4   5          60       RL         84.0    14260   Pave      IR1         Lvl   \n",
       "\n",
       "  Utilities LotConfig LandSlope Neighborhood Condition1 Condition2 BldgType  \\\n",
       "0    AllPub    Inside       Gtl      CollgCr       Norm       Norm     1Fam   \n",
       "1    AllPub       FR2       Gtl      Veenker      Feedr       Norm     1Fam   \n",
       "2    AllPub    Inside       Gtl      CollgCr       Norm       Norm     1Fam   \n",
       "3    AllPub    Corner       Gtl      Crawfor       Norm       Norm     1Fam   \n",
       "4    AllPub       FR2       Gtl      NoRidge       Norm       Norm     1Fam   \n",
       "\n",
       "  HouseStyle  OverallQual  OverallCond  YearBuilt  YearRemodAdd RoofStyle  \\\n",
       "0     2Story            7            5       2003          2003     Gable   \n",
       "1     1Story            6            8       1976          1976     Gable   \n",
       "2     2Story            7            5       2001          2002     Gable   \n",
       "3     2Story            7            5       1915          1970     Gable   \n",
       "4     2Story            8            5       2000          2000     Gable   \n",
       "\n",
       "  RoofMatl Exterior1st Exterior2nd MasVnrType  MasVnrArea ExterQual ExterCond  \\\n",
       "0  CompShg     VinylSd     VinylSd    BrkFace       196.0        Gd        TA   \n",
       "1  CompShg     MetalSd     MetalSd       None         0.0        TA        TA   \n",
       "2  CompShg     VinylSd     VinylSd    BrkFace       162.0        Gd        TA   \n",
       "3  CompShg     Wd Sdng     Wd Shng       None         0.0        TA        TA   \n",
       "4  CompShg     VinylSd     VinylSd    BrkFace       350.0        Gd        TA   \n",
       "\n",
       "  Foundation BsmtQual BsmtCond BsmtExposure BsmtFinType1  BsmtFinSF1  \\\n",
       "0      PConc       Gd       TA           No          GLQ         706   \n",
       "1     CBlock       Gd       TA           Gd          ALQ         978   \n",
       "2      PConc       Gd       TA           Mn          GLQ         486   \n",
       "3     BrkTil       TA       Gd           No          ALQ         216   \n",
       "4      PConc       Gd       TA           Av          GLQ         655   \n",
       "\n",
       "  BsmtFinType2  BsmtFinSF2  BsmtUnfSF  TotalBsmtSF Heating HeatingQC  \\\n",
       "0          Unf           0        150          856    GasA        Ex   \n",
       "1          Unf           0        284         1262    GasA        Ex   \n",
       "2          Unf           0        434          920    GasA        Ex   \n",
       "3          Unf           0        540          756    GasA        Gd   \n",
       "4          Unf           0        490         1145    GasA        Ex   \n",
       "\n",
       "  CentralAir Electrical  1stFlrSF  2ndFlrSF  LowQualFinSF  GrLivArea  \\\n",
       "0          Y      SBrkr       856       854             0       1710   \n",
       "1          Y      SBrkr      1262         0             0       1262   \n",
       "2          Y      SBrkr       920       866             0       1786   \n",
       "3          Y      SBrkr       961       756             0       1717   \n",
       "4          Y      SBrkr      1145      1053             0       2198   \n",
       "\n",
       "   BsmtFullBath  BsmtHalfBath  FullBath  HalfBath  BedroomAbvGr  KitchenAbvGr  \\\n",
       "0             1             0         2         1             3             1   \n",
       "1             0             1         2         0             3             1   \n",
       "2             1             0         2         1             3             1   \n",
       "3             1             0         1         0             3             1   \n",
       "4             1             0         2         1             4             1   \n",
       "\n",
       "  KitchenQual  TotRmsAbvGrd Functional  Fireplaces FireplaceQu GarageType  \\\n",
       "0          Gd             8        Typ           0         NaN     Attchd   \n",
       "1          TA             6        Typ           1          TA     Attchd   \n",
       "2          Gd             6        Typ           1          TA     Attchd   \n",
       "3          Gd             7        Typ           1          Gd     Detchd   \n",
       "4          Gd             9        Typ           1          TA     Attchd   \n",
       "\n",
       "   GarageYrBlt GarageFinish  GarageCars  GarageArea GarageQual GarageCond  \\\n",
       "0       2003.0          RFn           2         548         TA         TA   \n",
       "1       1976.0          RFn           2         460         TA         TA   \n",
       "2       2001.0          RFn           2         608         TA         TA   \n",
       "3       1998.0          Unf           3         642         TA         TA   \n",
       "4       2000.0          RFn           3         836         TA         TA   \n",
       "\n",
       "  PavedDrive  WoodDeckSF  OpenPorchSF  EnclosedPorch  3SsnPorch  ScreenPorch  \\\n",
       "0          Y           0           61              0          0            0   \n",
       "1          Y         298            0              0          0            0   \n",
       "2          Y           0           42              0          0            0   \n",
       "3          Y           0           35            272          0            0   \n",
       "4          Y         192           84              0          0            0   \n",
       "\n",
       "   PoolArea  MiscVal  MoSold  YrSold SaleType SaleCondition  SalePrice  \n",
       "0         0        0       2    2008       WD        Normal     208500  \n",
       "1         0        0       5    2007       WD        Normal     181500  \n",
       "2         0        0       9    2008       WD        Normal     223500  \n",
       "3         0        0       2    2006       WD       Abnorml     140000  \n",
       "4         0        0      12    2008       WD        Normal     250000  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>LandSlope</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Condition1</th>\n",
       "      <th>Condition2</th>\n",
       "      <th>BldgType</th>\n",
       "      <th>HouseStyle</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>RoofStyle</th>\n",
       "      <th>RoofMatl</th>\n",
       "      <th>Exterior1st</th>\n",
       "      <th>Exterior2nd</th>\n",
       "      <th>MasVnrType</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>ExterCond</th>\n",
       "      <th>Foundation</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>Heating</th>\n",
       "      <th>HeatingQC</th>\n",
       "      <th>CentralAir</th>\n",
       "      <th>Electrical</th>\n",
       "      <th>1stFlrSF</th>\n",
       "      <th>2ndFlrSF</th>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <th>GrLivArea</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <th>FullBath</th>\n",
       "      <th>HalfBath</th>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <th>Functional</th>\n",
       "      <th>Fireplaces</th>\n",
       "      <th>FireplaceQu</th>\n",
       "      <th>GarageType</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageCars</th>\n",
       "      <th>GarageArea</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>PavedDrive</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2003</td>\n",
       "      <td>2003</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>196.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>706</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>856</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>856</td>\n",
       "      <td>854</td>\n",
       "      <td>0</td>\n",
       "      <td>1710</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>8</td>\n",
       "      <td>Typ</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>548</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Veenker</td>\n",
       "      <td>Feedr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>1Story</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1976</td>\n",
       "      <td>1976</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>CBlock</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>978</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>284</td>\n",
       "      <td>1262</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>460</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2001</td>\n",
       "      <td>2002</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>162.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Mn</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>486</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>434</td>\n",
       "      <td>920</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>920</td>\n",
       "      <td>866</td>\n",
       "      <td>0</td>\n",
       "      <td>1786</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2</td>\n",
       "      <td>608</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Crawfor</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1915</td>\n",
       "      <td>1970</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>Wd Sdng</td>\n",
       "      <td>Wd Shng</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>BrkTil</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>No</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>216</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>540</td>\n",
       "      <td>756</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>961</td>\n",
       "      <td>756</td>\n",
       "      <td>0</td>\n",
       "      <td>1717</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>7</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Detchd</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>3</td>\n",
       "      <td>642</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>272</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>NoRidge</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>2000</td>\n",
       "      <td>2000</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Av</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>655</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0</td>\n",
       "      <td>490</td>\n",
       "      <td>1145</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1145</td>\n",
       "      <td>1053</td>\n",
       "      <td>0</td>\n",
       "      <td>2198</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>9</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>3</td>\n",
       "      <td>836</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>192</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street LotShape LandContour  \\\n",
       "0   1          60       RL         65.0     8450   Pave      Reg         Lvl   \n",
       "1   2          20       RL         80.0     9600   Pave      Reg         Lvl   \n",
       "2   3          60       RL         68.0    11250   Pave      IR1         Lvl   \n",
       "3   4          70       RL         60.0     9550   Pave      IR1         Lvl   \n",
       "4   5          60       RL         84.0    14260   Pave      IR1         Lvl   \n",
       "\n",
       "  Utilities LotConfig LandSlope Neighborhood Condition1 Condition2 BldgType  \\\n",
       "0    AllPub    Inside       Gtl      CollgCr       Norm       Norm     1Fam   \n",
       "1    AllPub       FR2       Gtl      Veenker      Feedr       Norm     1Fam   \n",
       "2    AllPub    Inside       Gtl      CollgCr       Norm       Norm     1Fam   \n",
       "3    AllPub    Corner       Gtl      Crawfor       Norm       Norm     1Fam   \n",
       "4    AllPub       FR2       Gtl      NoRidge       Norm       Norm     1Fam   \n",
       "\n",
       "  HouseStyle  OverallQual  OverallCond  YearBuilt  YearRemodAdd RoofStyle  \\\n",
       "0     2Story            7            5       2003          2003     Gable   \n",
       "1     1Story            6            8       1976          1976     Gable   \n",
       "2     2Story            7            5       2001          2002     Gable   \n",
       "3     2Story            7            5       1915          1970     Gable   \n",
       "4     2Story            8            5       2000          2000     Gable   \n",
       "\n",
       "  RoofMatl Exterior1st Exterior2nd MasVnrType  MasVnrArea ExterQual ExterCond  \\\n",
       "0  CompShg     VinylSd     VinylSd    BrkFace       196.0        Gd        TA   \n",
       "1  CompShg     MetalSd     MetalSd       None         0.0        TA        TA   \n",
       "2  CompShg     VinylSd     VinylSd    BrkFace       162.0        Gd        TA   \n",
       "3  CompShg     Wd Sdng     Wd Shng       None         0.0        TA        TA   \n",
       "4  CompShg     VinylSd     VinylSd    BrkFace       350.0        Gd        TA   \n",
       "\n",
       "  Foundation BsmtQual BsmtCond BsmtExposure BsmtFinType1  BsmtFinSF1  \\\n",
       "0      PConc       Gd       TA           No          GLQ         706   \n",
       "1     CBlock       Gd       TA           Gd          ALQ         978   \n",
       "2      PConc       Gd       TA           Mn          GLQ         486   \n",
       "3     BrkTil       TA       Gd           No          ALQ         216   \n",
       "4      PConc       Gd       TA           Av          GLQ         655   \n",
       "\n",
       "  BsmtFinType2  BsmtFinSF2  BsmtUnfSF  TotalBsmtSF Heating HeatingQC  \\\n",
       "0          Unf           0        150          856    GasA        Ex   \n",
       "1          Unf           0        284         1262    GasA        Ex   \n",
       "2          Unf           0        434          920    GasA        Ex   \n",
       "3          Unf           0        540          756    GasA        Gd   \n",
       "4          Unf           0        490         1145    GasA        Ex   \n",
       "\n",
       "  CentralAir Electrical  1stFlrSF  2ndFlrSF  LowQualFinSF  GrLivArea  \\\n",
       "0          Y      SBrkr       856       854             0       1710   \n",
       "1          Y      SBrkr      1262         0             0       1262   \n",
       "2          Y      SBrkr       920       866             0       1786   \n",
       "3          Y      SBrkr       961       756             0       1717   \n",
       "4          Y      SBrkr      1145      1053             0       2198   \n",
       "\n",
       "   BsmtFullBath  BsmtHalfBath  FullBath  HalfBath  BedroomAbvGr  KitchenAbvGr  \\\n",
       "0             1             0         2         1             3             1   \n",
       "1             0             1         2         0             3             1   \n",
       "2             1             0         2         1             3             1   \n",
       "3             1             0         1         0             3             1   \n",
       "4             1             0         2         1             4             1   \n",
       "\n",
       "  KitchenQual  TotRmsAbvGrd Functional  Fireplaces FireplaceQu GarageType  \\\n",
       "0          Gd             8        Typ           0         NaN     Attchd   \n",
       "1          TA             6        Typ           1          TA     Attchd   \n",
       "2          Gd             6        Typ           1          TA     Attchd   \n",
       "3          Gd             7        Typ           1          Gd     Detchd   \n",
       "4          Gd             9        Typ           1          TA     Attchd   \n",
       "\n",
       "   GarageYrBlt GarageFinish  GarageCars  GarageArea GarageQual GarageCond  \\\n",
       "0       2003.0          RFn           2         548         TA         TA   \n",
       "1       1976.0          RFn           2         460         TA         TA   \n",
       "2       2001.0          RFn           2         608         TA         TA   \n",
       "3       1998.0          Unf           3         642         TA         TA   \n",
       "4       2000.0          RFn           3         836         TA         TA   \n",
       "\n",
       "  PavedDrive  WoodDeckSF  OpenPorchSF  EnclosedPorch  3SsnPorch  ScreenPorch  \\\n",
       "0          Y           0           61              0          0            0   \n",
       "1          Y         298            0              0          0            0   \n",
       "2          Y           0           42              0          0            0   \n",
       "3          Y           0           35            272          0            0   \n",
       "4          Y         192           84              0          0            0   \n",
       "\n",
       "   PoolArea  MiscVal  MoSold  YrSold SaleType SaleCondition  SalePrice  \n",
       "0         0        0       2    2008       WD        Normal     208500  \n",
       "1         0        0       5    2007       WD        Normal     181500  \n",
       "2         0        0       9    2008       WD        Normal     223500  \n",
       "3         0        0       2    2006       WD       Abnorml     140000  \n",
       "4         0        0      12    2008       WD        Normal     250000  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = clean.deal_with_numeric_null()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Id             0\n",
       "MSSubClass     0\n",
       "MSZoning       0\n",
       "LotFrontage    0\n",
       "LotArea        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23b06b6ca20>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,7))\n",
    "sns.heatmap(df.isnull(),yticklabels = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23b06d83da0>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.loc[:,df.dtypes == np.int64].isnull(),yticklabels = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23b074cf8d0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.loc[:,df.dtypes == np.float64].isnull(),yticklabels = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23b0755fac8>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.loc[:,df.dtypes == np.object].isnull())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop('FireplaceQu',inplace=True,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.dropna(inplace=True,axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23b0781fc18>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.isnull(),yticklabels = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1338"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\dell\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\ipykernel_launcher.py:9: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  if __name__ == '__main__':\n"
     ]
    }
   ],
   "source": [
    "e = encoder(df)\n",
    "temp = e.start_encoding()\n",
    "df[temp.columns] = temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('Id',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = df.drop('SalePrice',axis = 1)\n",
    "Y = df['SalePrice']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>LandSlope</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Condition1</th>\n",
       "      <th>Condition2</th>\n",
       "      <th>BldgType</th>\n",
       "      <th>HouseStyle</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>RoofStyle</th>\n",
       "      <th>RoofMatl</th>\n",
       "      <th>Exterior1st</th>\n",
       "      <th>Exterior2nd</th>\n",
       "      <th>MasVnrType</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>ExterCond</th>\n",
       "      <th>Foundation</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>Heating</th>\n",
       "      <th>HeatingQC</th>\n",
       "      <th>CentralAir</th>\n",
       "      <th>Electrical</th>\n",
       "      <th>1stFlrSF</th>\n",
       "      <th>2ndFlrSF</th>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <th>GrLivArea</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <th>FullBath</th>\n",
       "      <th>HalfBath</th>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <th>Functional</th>\n",
       "      <th>Fireplaces</th>\n",
       "      <th>GarageType</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageCars</th>\n",
       "      <th>GarageArea</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>PavedDrive</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>60</td>\n",
       "      <td>3</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2003</td>\n",
       "      <td>2003</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>196.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>706</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>150</td>\n",
       "      <td>856</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>856</td>\n",
       "      <td>854</td>\n",
       "      <td>0</td>\n",
       "      <td>1710</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>548</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
       "      <td>3</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1976</td>\n",
       "      <td>1976</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>978</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>284</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>460</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>60</td>\n",
       "      <td>3</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2001</td>\n",
       "      <td>2002</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>162.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>486</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>434</td>\n",
       "      <td>920</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>920</td>\n",
       "      <td>866</td>\n",
       "      <td>0</td>\n",
       "      <td>1786</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>608</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>70</td>\n",
       "      <td>3</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1915</td>\n",
       "      <td>1970</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>216</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>540</td>\n",
       "      <td>756</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>961</td>\n",
       "      <td>756</td>\n",
       "      <td>0</td>\n",
       "      <td>1717</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>642</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>272</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>60</td>\n",
       "      <td>3</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>2000</td>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "      <td>350.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>655</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>490</td>\n",
       "      <td>1145</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1145</td>\n",
       "      <td>1053</td>\n",
       "      <td>0</td>\n",
       "      <td>2198</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>836</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>192</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>8</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    MSSubClass  MSZoning  LotFrontage  LotArea  Street  LotShape  LandContour  \\\n",
       "Id                                                                              \n",
       "1           60         3         65.0     8450       1         3            3   \n",
       "2           20         3         80.0     9600       1         3            3   \n",
       "3           60         3         68.0    11250       1         0            3   \n",
       "4           70         3         60.0     9550       1         0            3   \n",
       "5           60         3         84.0    14260       1         0            3   \n",
       "\n",
       "    Utilities  LotConfig  LandSlope  Neighborhood  Condition1  Condition2  \\\n",
       "Id                                                                          \n",
       "1           0          4          0             5           2           2   \n",
       "2           0          2          0            24           1           2   \n",
       "3           0          4          0             5           2           2   \n",
       "4           0          0          0             6           2           2   \n",
       "5           0          2          0            15           2           2   \n",
       "\n",
       "    BldgType  HouseStyle  OverallQual  OverallCond  YearBuilt  YearRemodAdd  \\\n",
       "Id                                                                            \n",
       "1          0           5            7            5       2003          2003   \n",
       "2          0           2            6            8       1976          1976   \n",
       "3          0           5            7            5       2001          2002   \n",
       "4          0           5            7            5       1915          1970   \n",
       "5          0           5            8            5       2000          2000   \n",
       "\n",
       "    RoofStyle  RoofMatl  Exterior1st  Exterior2nd  MasVnrType  MasVnrArea  \\\n",
       "Id                                                                          \n",
       "1           1         1           11           13           1       196.0   \n",
       "2           1         1            7            8           2         0.0   \n",
       "3           1         1           11           13           1       162.0   \n",
       "4           1         1           12           15           2         0.0   \n",
       "5           1         1           11           13           1       350.0   \n",
       "\n",
       "    ExterQual  ExterCond  Foundation  BsmtQual  BsmtCond  BsmtExposure  \\\n",
       "Id                                                                       \n",
       "1           2          3           2         2         3             3   \n",
       "2           3          3           1         2         3             1   \n",
       "3           2          3           2         2         3             2   \n",
       "4           3          3           0         3         1             3   \n",
       "5           2          3           2         2         3             0   \n",
       "\n",
       "    BsmtFinType1  BsmtFinSF1  BsmtFinType2  BsmtFinSF2  BsmtUnfSF  \\\n",
       "Id                                                                  \n",
       "1              2         706             5           0        150   \n",
       "2              0         978             5           0        284   \n",
       "3              2         486             5           0        434   \n",
       "4              0         216             5           0        540   \n",
       "5              2         655             5           0        490   \n",
       "\n",
       "    TotalBsmtSF  Heating  HeatingQC  CentralAir  Electrical  1stFlrSF  \\\n",
       "Id                                                                      \n",
       "1           856        0          0           1           4       856   \n",
       "2          1262        0          0           1           4      1262   \n",
       "3           920        0          0           1           4       920   \n",
       "4           756        0          2           1           4       961   \n",
       "5          1145        0          0           1           4      1145   \n",
       "\n",
       "    2ndFlrSF  LowQualFinSF  GrLivArea  BsmtFullBath  BsmtHalfBath  FullBath  \\\n",
       "Id                                                                            \n",
       "1        854             0       1710             1             0         2   \n",
       "2          0             0       1262             0             1         2   \n",
       "3        866             0       1786             1             0         2   \n",
       "4        756             0       1717             1             0         1   \n",
       "5       1053             0       2198             1             0         2   \n",
       "\n",
       "    HalfBath  BedroomAbvGr  KitchenAbvGr  KitchenQual  TotRmsAbvGrd  \\\n",
       "Id                                                                    \n",
       "1          1             3             1            2             8   \n",
       "2          0             3             1            3             6   \n",
       "3          1             3             1            2             6   \n",
       "4          0             3             1            2             7   \n",
       "5          1             4             1            2             9   \n",
       "\n",
       "    Functional  Fireplaces  GarageType  GarageYrBlt  GarageFinish  GarageCars  \\\n",
       "Id                                                                              \n",
       "1            6           0           1       2003.0             1           2   \n",
       "2            6           1           1       1976.0             1           2   \n",
       "3            6           1           1       2001.0             1           2   \n",
       "4            6           1           5       1998.0             2           3   \n",
       "5            6           1           1       2000.0             1           3   \n",
       "\n",
       "    GarageArea  GarageQual  GarageCond  PavedDrive  WoodDeckSF  OpenPorchSF  \\\n",
       "Id                                                                            \n",
       "1          548           4           4           2           0           61   \n",
       "2          460           4           4           2         298            0   \n",
       "3          608           4           4           2           0           42   \n",
       "4          642           4           4           2           0           35   \n",
       "5          836           4           4           2         192           84   \n",
       "\n",
       "    EnclosedPorch  3SsnPorch  ScreenPorch  PoolArea  MiscVal  MoSold  YrSold  \\\n",
       "Id                                                                             \n",
       "1               0          0            0         0        0       2    2008   \n",
       "2               0          0            0         0        0       5    2007   \n",
       "3               0          0            0         0        0       9    2008   \n",
       "4             272          0            0         0        0       2    2006   \n",
       "5               0          0            0         0        0      12    2008   \n",
       "\n",
       "    SaleType  SaleCondition  \n",
       "Id                           \n",
       "1          8              4  \n",
       "2          8              4  \n",
       "3          8              4  \n",
       "4          8              0  \n",
       "5          8              4  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "X['GarageYrBlt'] = X['GarageYrBlt'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'OverallQual': 0.7835456113843182,\n",
       " 'YearBuilt': 0.5042971750930905,\n",
       " 'YearRemodAdd': 0.5014353821077963,\n",
       " 'ExterQual': -0.648023475225641,\n",
       " 'BsmtQual': -0.6118334877813126,\n",
       " 'TotalBsmtSF': 0.6020422814414286,\n",
       " '1stFlrSF': 0.6047144846292781,\n",
       " 'GrLivArea': 0.7117061511024302,\n",
       " 'FullBath': 0.5693126295659868,\n",
       " 'KitchenQual': -0.6168669685619623,\n",
       " 'TotRmsAbvGrd': 0.5518206950104736,\n",
       " 'GarageFinish': -0.5082316799671487,\n",
       " 'GarageCars': 0.6401543580531921,\n",
       " 'GarageArea': 0.6075353838509898}"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d = corr_elemination(X,Y)\n",
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "cons = list()\n",
    "for x,y in d.items():\n",
    "    cons.append(x)\n",
    "x = X[cons]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>1stFlrSF</th>\n",
       "      <th>GrLivArea</th>\n",
       "      <th>FullBath</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageCars</th>\n",
       "      <th>GarageArea</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7</td>\n",
       "      <td>2003</td>\n",
       "      <td>2003</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>856</td>\n",
       "      <td>856</td>\n",
       "      <td>1710</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6</td>\n",
       "      <td>1976</td>\n",
       "      <td>1976</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>1262</td>\n",
       "      <td>1262</td>\n",
       "      <td>1262</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7</td>\n",
       "      <td>2001</td>\n",
       "      <td>2002</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>920</td>\n",
       "      <td>920</td>\n",
       "      <td>1786</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7</td>\n",
       "      <td>1915</td>\n",
       "      <td>1970</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>756</td>\n",
       "      <td>961</td>\n",
       "      <td>1717</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>7</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8</td>\n",
       "      <td>2000</td>\n",
       "      <td>2000</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1145</td>\n",
       "      <td>1145</td>\n",
       "      <td>2198</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>836</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    OverallQual  YearBuilt  YearRemodAdd  ExterQual  BsmtQual  TotalBsmtSF  \\\n",
       "Id                                                                           \n",
       "1             7       2003          2003          2         2          856   \n",
       "2             6       1976          1976          3         2         1262   \n",
       "3             7       2001          2002          2         2          920   \n",
       "4             7       1915          1970          3         3          756   \n",
       "5             8       2000          2000          2         2         1145   \n",
       "\n",
       "    1stFlrSF  GrLivArea  FullBath  KitchenQual  TotRmsAbvGrd  GarageFinish  \\\n",
       "Id                                                                           \n",
       "1        856       1710         2            2             8             1   \n",
       "2       1262       1262         2            3             6             1   \n",
       "3        920       1786         2            2             6             1   \n",
       "4        961       1717         1            2             7             2   \n",
       "5       1145       2198         2            2             9             1   \n",
       "\n",
       "    GarageCars  GarageArea  \n",
       "Id                          \n",
       "1            2         548  \n",
       "2            2         460  \n",
       "3            2         608  \n",
       "4            3         642  \n",
       "5            3         836  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Machine learning model "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "l = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "x_train,x_test,y_train,y_test = train_test_split(x,Y,test_size = 0.2,random_state = 40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=None,\n",
       "         normalize=False)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "73.27087336077194"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "l.score(x_test,y_test)*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "predicted_vals = l.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "Predicted_VS_Actual = pd.DataFrame({'Predicted' : predicted_vals,'Actual' : y_test})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "Predicted_VS_Actual['Predicted'] = Predicted_VS_Actual['Predicted'].map(np.round)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Predicted</th>\n",
       "      <th>Actual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1201</th>\n",
       "      <td>82884.0</td>\n",
       "      <td>116050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>828</th>\n",
       "      <td>215642.0</td>\n",
       "      <td>189000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>218729.0</td>\n",
       "      <td>194500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>358470.0</td>\n",
       "      <td>395192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>217767.0</td>\n",
       "      <td>192000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Predicted  Actual\n",
       "Id                     \n",
       "1201    82884.0  116050\n",
       "828    215642.0  189000\n",
       "238    218729.0  194500\n",
       "988    358470.0  395192\n",
       "1083   217767.0  192000"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Predicted_VS_Actual.head()"
   ]
  }
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